State-of-the-art review on advancements of data mining in structural health monitoring
To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …
statistical methods have been utilized in a remarkable number of structural health monitoring …
Recent advances and applications of surrogate models for finite element method computations: a review
J Kudela, R Matousek - Soft Computing, 2022 - Springer
The utilization of surrogate models to approximate complex systems has recently gained
increased popularity. Because of their capability to deal with black-box problems and lower …
increased popularity. Because of their capability to deal with black-box problems and lower …
Artificial intelligence in prognostics and health management of engineering systems
S Ochella, M Shafiee, F Dinmohammadi - Engineering Applications of …, 2022 - Elsevier
Prognostics and health management (PHM) has become a crucial aspect of the
management of engineering systems and structures, where sensor hardware and decision …
management of engineering systems and structures, where sensor hardware and decision …
A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction
Vehicle actions represent the main operational loading for various types of bridges. It is
essential to conduct random vibration analysis due to the unavoidable uncertainties arising …
essential to conduct random vibration analysis due to the unavoidable uncertainties arising …
Value of information analysis in civil and infrastructure engineering: a review
The concept of Value of Information (VoI) has attracted significant attentions within the civil
engineering community over especially the last decade. Triggered by the increasing focus …
engineering community over especially the last decade. Triggered by the increasing focus …
Algorithms and techniques for the structural health monitoring of bridges: Systematic literature review
Structural health monitoring (SHM) systems are used to analyze the health of infrastructures
such as bridges, using data from various types of sensors. While SHM systems consist of …
such as bridges, using data from various types of sensors. While SHM systems consist of …
Bayesian model updating with finite element vs surrogate models: Application to a miter gate structural system
Bayesian finite element (FE) model updating using direct model evaluations of large-scale
high-fidelity FE models is extremely computationally expensive. Surrogate models can be …
high-fidelity FE models is extremely computationally expensive. Surrogate models can be …
[HTML][HTML] A probabilistic risk-based decision framework for structural health monitoring
Obtaining the ability to make informed decisions regarding the operation and maintenance
of structures, provides a major incentive for the implementation of structural health …
of structures, provides a major incentive for the implementation of structural health …
Application of data-driven surrogate models in structural engineering: a literature review
In recent times, there has been an increasing prevalence of surrogate models and
metamodeling techniques in approximating the responses of complex systems. These …
metamodeling techniques in approximating the responses of complex systems. These …
[HTML][HTML] A Bayesian methodology for localising acoustic emission sources in complex structures
In the field of structural health monitoring (SHM), the acquisition of acoustic emissions to
localise damage sources has emerged as a popular approach. Despite recent advances …
localise damage sources has emerged as a popular approach. Despite recent advances …